Simpson’s rule based accurate mathematical modelling of photovoltaic cell using multi-objective genetic algorithm for hardware verification

Abstract

The behaviour and effective performance of solar cell is represented by Triple Diode Solar Cell Module (TDSCM) circuit with five parameters for different environmental conditions. The equations described the solar modules behaviour are usually implicit in nature and the parameter extraction was very complexity. From the Photovoltaic (PV) module data sheet, one can identify the four equations applying to single, double, and triple diode parameters. For getting fifth equation researchers have gone with several approximations, which concludes the computation complexity, convergence problem, and low accuracy issues. In the proposed work the fifth equation are framed under the area characteristics curve (V-I & P-V) concept using Simpson’s approximation. To find which PV module is less accuracy and non-linearity consideration for the performance level. Therefore, to overcome these issues the multi-objective Genetic Algorithm (GA) optimization method are prescribed to frame the fifth equation of the Simpson’s rules. This works improved non-linearity performance and gives the high accuracy modelling compare to other single, double diode methods.